Enhancing uterine contraction detection through novel EHG signal processing: a pilot study leveraging the relationship between slow and fast wave components to improve signal quality and noise resilience

利用新型 EHG 信号处理技术增强子宫收缩检测:一项利用慢波和快波成分之间关系来提高信号质量和抗噪能力的初步研究

阅读:1

Abstract

Uterine contractions, driven by complex electrical activities within the uterine smooth muscle cells, play a critical role in labor and delivery. Various techniques, including EHG and EMMI, have been developed to record and image uterine electrical activities. Both EHG and EMMI use a bandpass filter (fast wave 0.34-1Hz) to preserve uterine contraction activities. However, high-frequency signals are usually weak and are prone to multiple sources of noise and artifacts, significantly impacting the accuracy of contraction detection and subsequent analysis of long- and short-distance signaling in the laboring uterus. Existing methods, such as Zero-Crossing-Rate (ZCR) and Teager-Kaiser Energy Operator (TKEO), employ the transformation of fast wave signals to detect uterine contractions and are still limited by the EHG signal quality. This work proposed a novel method that combines high-frequency (fast wave, 0.34-1Hz) and low-frequency (slow wave, 0.01-0.1Hz) components of uterine electrical signals to generate enhanced EHG signals. Incorporating slow-wave signals offers additional information rather than relying solely on fast wave signals like ZCR and TKEO. Our approach utilizes the stability of slow wave signals to enhance the more noise-prone fast wave signals. This method significantly improves the quality of uterine contraction detection, as evidenced by enhanced signal contrast between contractions and baseline activity. The improved signals enable more accurate detection of contractions and more detailed spatial analysis of uterine contraction propagation. This signal enhancement technique holds great potential for advancing the understanding of long- and short-distance signaling during labor, paving the way for more precise labor management and better maternal-fetal outcomes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。